2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)最新文献

{"title":"Regression Fuzzing for Deep Learning Systems","authors":"Hanmo You, Zan Wang, Junjie Chen, Shuang Liu, Shuochuan Li","doi":"10.1109/ICSE48619.2023.00019","DOIUrl":"https://doi.org/10.1109/ICSE48619.2023.00019","url":null,"abstract":"Deep learning (DL) Systems have been widely used in various domains. Similar to traditional software, DL system evolution may also incur regression faults. To find the regression faults between versions of a DL system, we propose a novel regression fuzzing technique called DRFuzz, which facilitates generating inputs that trigger diverse regression faults and have high fidelity. To enhance the diversity of the found regression faults, DRFuzz proposes a diversity-oriented test criterion to explore as many faulty behaviors as possible. Then, DRFuzz incorporates the GAN model to guarantee the fidelity of generated test inputs. We conduct an extensive study on four subjects in four regression scenarios of DL systems. The experimental results demonstrate the superiority of DRFuzz over the two compared state-of-the-art approaches, with an average improvement of 1,177% and 539% in terms of the number of detected regression faults.","PeriodicalId":376379,"journal":{"name":"2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)","volume":"4303 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130618229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Safe Low-Level Code Without Overhead is Practical","authors":"Solal Pirelli, George Candea","doi":"10.1109/ICSE48619.2023.00183","DOIUrl":"https://doi.org/10.1109/ICSE48619.2023.00183","url":null,"abstract":"Developers write low-level systems code in unsafe programming languages due to performance concerns. The lack of safety causes bugs and vulnerabilities that safe languages avoid. We argue that safety without run-time overhead is possible through type invariants that prove the safety of potentially unsafe operations. We empirically show that Rust and C# can be extended with such features to implement safe network device drivers without run-time overhead, and that Ada has these features already.","PeriodicalId":376379,"journal":{"name":"2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)","volume":"478 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133910556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"BSHUNTER: Detecting and Tracing Defects of Bitcoin Scripts","authors":"Peilin Zheng, Xiapu Luo, Zibin Zheng","doi":"10.1109/ICSE48619.2023.00037","DOIUrl":"https://doi.org/10.1109/ICSE48619.2023.00037","url":null,"abstract":"Supporting the most popular cryptocurrency, the Bitcoin platform allows its transactions to be programmable via its scripts. Defects in Bitcoin scripts will make users lose their bitcoins. However, there are few studies on the defects of Bitcoin scripts. In this paper, we conduct the first systematic investigation on the defects of Bitcoin scripts through three steps, including defect definition, defect detection, and exploitation tracing. First, we define six typical defects of scripts in Bitcoin history, namely unbinded-txid, simple-key, useless-sig, uncertain-sig, impossible-key, and never-true. Three are inspired by the community, and three are new from us. Second, we develop a tool to discover Bitcoin scripts with any of typical defects based on symbolic execution and enhanced by historical exact scripts. By analyzing all Bitcoin transactions from Oct. 2009 to Aug. 2022, we find that 383,544 transaction outputs are paid to the Bitcoin scripts with defects. The total amount of them is 3,115.43 BTC, which is around 60 million dollars at present. Third, in order to trace the exploitation of the defects, we instrument the Bitcoin VM to record the traces of the real-world spending transactions of the buggy scripts. We find that 84,130 output scripts are exploited. The implementation and non-harmful datasets are released.","PeriodicalId":376379,"journal":{"name":"2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134074189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Demystifying Issues, Challenges, and Solutions for Multilingual Software Development","authors":"Haoran Yang, Weile Lian, Shaowei Wang, Haipeng Cai","doi":"10.1109/ICSE48619.2023.00157","DOIUrl":"https://doi.org/10.1109/ICSE48619.2023.00157","url":null,"abstract":"Developing a software project using multiple languages together has been a dominant practice for years. Yet it remains unclear what issues developers encounter during the development, which challenges cause the issues, and what solutions developers receive. In this paper, we aim to answer these questions via a study on developer discussions on Stack Overflow. By manually analyzing 586 highly relevant posts spanning 14 years, we observed a large variety (11 categories) of issues, dominated by those with interfacing and data handling among different languages. Behind these issues, we found that a major challenge developers faced is the diversity and complexity in multilingual code building and interoperability. Another key challenge lies in developers' lack of particular technical background on the diverse features of various languages (e.g., threading and memory management mechanisms). Meanwhile, Stack Overflow itself served as a key source of solutions to these challenges-the majority (73%) of the posts received accepted answers eventually, and most in a week (36.5% within 24 hours and 25% in the next 6 days). Based on our findings on these issues, challenges, and solutions, we provide actionable insights and suggestions for both multi-language software researchers and developers.","PeriodicalId":376379,"journal":{"name":"2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129688418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On the Self-Governance and Episodic Changes in Apache Incubator Projects: An Empirical Study","authors":"Likang Yin, Xiyu Zhang, V. Filkov","doi":"10.1109/ICSE48619.2023.00066","DOIUrl":"https://doi.org/10.1109/ICSE48619.2023.00066","url":null,"abstract":"Sustainable Open Source Software (OSS) projects are characterized by the ability to attract new project members and maintain an energetic project community. Building sustainable OSS projects from a nascent state requires effective project governance and socio-technical structure to be interleaved, in a complex and dynamic process. Although individual disciplines have studied each separately, little is known about how governance and software development work together in practice toward sustainability. Prior work has shown that many OSS projects experience large, episodic changes over short periods of time, which can propel them or drag them down. However, sustainable projects typically manage to come out unscathed from such changes, while others do not. The natural questions arise: Can we identify the back-and-forth between governance and socio-technical structure that lead to sustainability following episodic events? And, how about those that do not lead to sustainability? From a data set of social, technical, and policy digital traces from 262 sustainability-labeled ASF incubator projects, here we employ a large-scale empirical study to characterize episodic changes in socio-technical aspects measured by Change Intervals (CI), governance rules and regulations in a form of Institutional Statements (IS), and the temporal relationships between them. We find that sustainable projects during episodic changes can adapt themselves to institutional statements more efficiently, and that institutional discussions can lead to episodic changes intervals in socio-technical aspects of the projects, and vice versa. In practice, these results can provide timely guidance beyond socio-technical considerations, adding rules and regulations in the mix, toward a unified analytical framework for OSS project sustainability.","PeriodicalId":376379,"journal":{"name":"2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132306757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CodaMosa: Escaping Coverage Plateaus in Test Generation with Pre-trained Large Language Models","authors":"Caroline Lemieux, J. Inala, Shuvendu K. Lahiri, S. Sen","doi":"10.1109/ICSE48619.2023.00085","DOIUrl":"https://doi.org/10.1109/ICSE48619.2023.00085","url":null,"abstract":"Search-based software testing (SBST) generates high-coverage test cases for programs under test with a combination of test case generation and mutation. SBST's performance relies on there being a reasonable probability of generating test cases that exercise the core logic of the program under test. Given such test cases, SBST can then explore the space around them to exercise various parts of the program. This paper explores whether Large Language Models (LLMs) of code, such as OpenAI's Codex, can be used to help SBST's exploration. Our proposed algorithm, CodaMosa, conducts SBST until its coverage improvements stall, then asks Codex to provide example test cases for under-covered functions. These examples help SBST redirect its search to more useful areas of the search space. On an evaluation over 486 benchmarks, CodaMosa achieves statistically significantly higher coverage on many more benchmarks (173 and 279) than it reduces coverage on (10 and 4), compared to SBST and LLM-only baselines.","PeriodicalId":376379,"journal":{"name":"2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123930504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Learning Seed-Adaptive Mutation Strategies for Greybox Fuzzing","authors":"M. Lee, Sooyoung Cha, Hakjoo Oh","doi":"10.1109/ICSE48619.2023.00043","DOIUrl":"https://doi.org/10.1109/ICSE48619.2023.00043","url":null,"abstract":"In this paper, we present a technique for learning seed-adaptive mutation strategies for fuzzers. The performance of mutation-based fuzzers highly depends on the mutation strategy that specifies the probability distribution of selecting mutation methods. As a result, developing an effective mutation strategy has received much attention recently, and program-adaptive techniques, which observe the behavior of the target program to learn the optimized mutation strategy per program, have become a trending approach to achieve better performance. They, however, still have a major limitation; they disregard the impacts of different characteristics of seed inputs which can lead to explore deeper program locations. To address this limitation, we present SEAMFUZZ, a novel fuzzing technique that automatically captures the characteristics of individual seed inputs and applies different mutation strategies for different seed inputs. By capturing the syntactic and semantic similarities between seed inputs, SEAMFUZZ clusters them into proper groups and learns effective mutation strategies tailored for each seed cluster by using the customized Thompson sampling algorithm. Experimental results show that SEAMFUZZ improves both the path-discovering and bug-finding abilities of state-of-the-art fuzzers on real-world programs.","PeriodicalId":376379,"journal":{"name":"2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)","volume":"171 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121098024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying Key Classes for Initial Software Comprehension: Can We Do It Better?","authors":"Weifeng Pan, Xin Du, Ming Hua, Dae-Kyoo Kim, Zijiang Yang","doi":"10.1109/ICSE48619.2023.00160","DOIUrl":"https://doi.org/10.1109/ICSE48619.2023.00160","url":null,"abstract":"Key classes are excellent starting points for developers, especially newcomers, to comprehend an unknown software system. Though many unsupervised key class identification approaches have been proposed in the literature by representing software as class dependency networks (aka software networks) and using some network metrics (e.g., h-index, a-index, and coreness), they are never aware of the field where the nodes exist and the effect of the field on the importance of the nodes in it. According to the classic field theory in physics, every material particle is in a field through which they exert an impact on other particles in the field via non-contact interactions (e.g., electromagnetic force, gravity, and nuclear force). Similarly, every node in a software network might also exist in a field, which might affect the importance of class nodes in it. In this paper, we propose an approach, iFit, to identify key classes in object-oriented software systems. First, we represent software as a CSNWD (Weighted Directed Class-level Software Network) to capture the topological structure of software, including classes, their couplings, and the direction and strength of couplings. Second, we assume that the nodes in the CSNWD exist in a gravitation-like field and propose a new metric, CG (Cumulative Gravitation-like importance), to measure the importance of classes. CG is inspired by Newton's gravitational formula and uses the PageRank value computed by a biased-PageRank algorithm as the masses of classes. Finally, classes in the system are sorted in descending order according to their CG values, and a cutoff is utilized, that is, the top-ranked classes are recommended as key classes. The experiments were performed on a data set composed of six open-source Java systems from the literature. The results show that iFit is superior to the baseline approaches on 93.75% of the total cases, and is scalable to large-scale software systems. Besides, we find that iFit is neutral to the weighting mechanisms used to assign the weights for different coupling types in the CSNWD, that is, when applying iFit to identify key classes, we can use any one of the weighting mechanisms.","PeriodicalId":376379,"journal":{"name":"2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122669046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RAT: A Refactoring-Aware Traceability Model for Bug Localization","authors":"Feifei Niu, W. K. Assunção, LiGuo Huang, Christoph Mayr-Dorn, Jidong Ge, Bin Luo, Alexander Egyed","doi":"10.1109/ICSE48619.2023.00028","DOIUrl":"https://doi.org/10.1109/ICSE48619.2023.00028","url":null,"abstract":"A large number of bug reports are created during the evolution of a software system. Locating the source code files that need to be changed in order to fix these bugs is a challenging task. Information retrieval-based bug localization techniques do so by correlating bug reports with historical information about the source code (e.g., previously resolved bug reports, commit logs). These techniques have shown to be efficient and easy to use. However, one flaw that is nearly omnipresent in all these techniques is that they ignore code refactorings. Code refactorings are common during software system evolution, but from the perspective of typical version control systems, they break the code history. For example, a class when renamed then appears as two separate classes with separate histories. Obviously, this is a problem that affects any technique that leverages code history. This paper proposes a refactoring-aware traceability model to keep track of the code evolution history. With this model, we reconstruct the code history by analyzing the impact of code refactorings to correctly stitch together what would otherwise be a fragmented history. To demonstrate that a refactoring aware history is indeed beneficial, we investigated three widely adopted bug localization techniques that make use of code history, which are important components in existing approaches. Our evaluation on 11 open source projects shows that taking code refactorings into account significantly improves the results of these bug localization techniques without significant changes to the techniques themselves. The more refactorings are used in a project, the stronger the benefit we observed. Based on our findings, we believe that much of the state of the art leveraging code history should benefit from our work.","PeriodicalId":376379,"journal":{"name":"2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124739916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Twins or False Friends? A Study on Energy Consumption and Performance of Configurable Software","authors":"Max Weber, Christian Kaltenecker, Florian Sattler, S. Apel, Norbert Siegmund","doi":"10.1109/ICSE48619.2023.00177","DOIUrl":"https://doi.org/10.1109/ICSE48619.2023.00177","url":null,"abstract":"Reducing energy consumption of software is an increasingly important objective, and there has been extensive research for data centers, smartphones, and embedded systems. However, when it comes to software, we lack working tools and methods to directly reduce energy consumption. For performance, we can resort to configuration options for tuning response time or throughput of a software system. For energy, it is still unclear whether the underlying assumption that runtime performance correlates with energy consumption holds, especially when it comes to optimization via configuration. To evaluate whether and to what extent this assumption is valid for configurable software systems, we conducted the largest empirical study of this kind to date. First, we searched the literature for reports on whether and why runtime performance correlates with energy consumption. We obtained a mixed, even contradicting picture from positive to negative correlation, and that configurability has not been considered yet as a factor for this variance. Second, we measured and analyzed both the runtime performance and energy consumption of 14 real-world software systems. We found that, in many cases, it depends on the software system's configuration whether runtime performance and energy consumption correlate and that, typically, only few configuration options influence the degree of correlation. A fine-grained analysis at the function level revealed that only few functions are relevant to obtain an accurate proxy for energy consumption and that, knowing them, allows one to infer individual transfer factors between runtime performance and energy consumption.","PeriodicalId":376379,"journal":{"name":"2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127230560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}